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Optimization of isocenter position for multiple targets with nonuniform‐margin expansion

PURPOSE: The single isocenter for multiple‐target (SIMT) technique has become a popular treatment technique for multiple brain metastases. We have implemented a method to obtain a nonuniform margin for SIMT technique. In this study, we further propose a method to determine the isocenter position so...

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Autores principales: Miao, Junjie, Xu, Yingjie, Dai, Jianrong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018668/
https://www.ncbi.nlm.nih.gov/pubmed/36924428
http://dx.doi.org/10.1002/acm2.13853
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author Miao, Junjie
Xu, Yingjie
Dai, Jianrong
author_facet Miao, Junjie
Xu, Yingjie
Dai, Jianrong
author_sort Miao, Junjie
collection PubMed
description PURPOSE: The single isocenter for multiple‐target (SIMT) technique has become a popular treatment technique for multiple brain metastases. We have implemented a method to obtain a nonuniform margin for SIMT technique. In this study, we further propose a method to determine the isocenter position so that the total expanded margin volume is minimal. MATERIALS AND METHOD: Based on a statistical model, the relationship between nonuniform margin and the distance d (from isocenter to target point), setup uncertainties, and significance level was established. Due to the existence of rotational error, there is a nonlinear relationship between the margin volume and the isocenter position. Using numerical simulation, we study the relationship between optimal isocenter position and translational error, rotational error, and target size. In order to find the optimal isocenter position quickly, adaptive simulated annealing (ASA) algorithm was used. This method was implemented in the Pinnacle(3) treatment planning system and compared with isocenter at center‐of‐geometric (COG), center‐of‐volume (COV), and center‐of‐surface (COS). Ten patients with multiple brain metastasis targets treated with the SIMT technique was selected for evaluation. RESULTS: When the size of tumors is equal, the optimal isocenter obtained by ASA and numerical simulation coincides with COG, COV, and COS. When the size of tumors is different, the optimal isocenter is close to the large tumor. The position of COS point is closer to the optimal point than the COV point for nearly all cases. Moreover, in some cases the COS point can be approximately selected as the optimal point. The ASA algorithm can reduce the calculating time from several hours to tens of seconds for three or more tumors. Using multiple brain metastases targets, a series of volume difference and calculating time were obtained for various tumor number, tumor size, and separation distances. Compared with the margin volume with isocenter at COG, the margin volume for optimal point can be reduced by up to 27.7%. CONCLUSION: Optimal treatment isocenter selection of multiple targets with large differences could reduce the total margin volume. ASA algorithm can significantly improve the speed of finding the optimal isocenter. This method can be used for clinical isocenter selection and is useful for the protection of normal tissue nearby.
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spelling pubmed-100186682023-03-17 Optimization of isocenter position for multiple targets with nonuniform‐margin expansion Miao, Junjie Xu, Yingjie Dai, Jianrong J Appl Clin Med Phys Radiation Oncology Physics PURPOSE: The single isocenter for multiple‐target (SIMT) technique has become a popular treatment technique for multiple brain metastases. We have implemented a method to obtain a nonuniform margin for SIMT technique. In this study, we further propose a method to determine the isocenter position so that the total expanded margin volume is minimal. MATERIALS AND METHOD: Based on a statistical model, the relationship between nonuniform margin and the distance d (from isocenter to target point), setup uncertainties, and significance level was established. Due to the existence of rotational error, there is a nonlinear relationship between the margin volume and the isocenter position. Using numerical simulation, we study the relationship between optimal isocenter position and translational error, rotational error, and target size. In order to find the optimal isocenter position quickly, adaptive simulated annealing (ASA) algorithm was used. This method was implemented in the Pinnacle(3) treatment planning system and compared with isocenter at center‐of‐geometric (COG), center‐of‐volume (COV), and center‐of‐surface (COS). Ten patients with multiple brain metastasis targets treated with the SIMT technique was selected for evaluation. RESULTS: When the size of tumors is equal, the optimal isocenter obtained by ASA and numerical simulation coincides with COG, COV, and COS. When the size of tumors is different, the optimal isocenter is close to the large tumor. The position of COS point is closer to the optimal point than the COV point for nearly all cases. Moreover, in some cases the COS point can be approximately selected as the optimal point. The ASA algorithm can reduce the calculating time from several hours to tens of seconds for three or more tumors. Using multiple brain metastases targets, a series of volume difference and calculating time were obtained for various tumor number, tumor size, and separation distances. Compared with the margin volume with isocenter at COG, the margin volume for optimal point can be reduced by up to 27.7%. CONCLUSION: Optimal treatment isocenter selection of multiple targets with large differences could reduce the total margin volume. ASA algorithm can significantly improve the speed of finding the optimal isocenter. This method can be used for clinical isocenter selection and is useful for the protection of normal tissue nearby. John Wiley and Sons Inc. 2022-11-21 /pmc/articles/PMC10018668/ /pubmed/36924428 http://dx.doi.org/10.1002/acm2.13853 Text en © 2022 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Radiation Oncology Physics
Miao, Junjie
Xu, Yingjie
Dai, Jianrong
Optimization of isocenter position for multiple targets with nonuniform‐margin expansion
title Optimization of isocenter position for multiple targets with nonuniform‐margin expansion
title_full Optimization of isocenter position for multiple targets with nonuniform‐margin expansion
title_fullStr Optimization of isocenter position for multiple targets with nonuniform‐margin expansion
title_full_unstemmed Optimization of isocenter position for multiple targets with nonuniform‐margin expansion
title_short Optimization of isocenter position for multiple targets with nonuniform‐margin expansion
title_sort optimization of isocenter position for multiple targets with nonuniform‐margin expansion
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018668/
https://www.ncbi.nlm.nih.gov/pubmed/36924428
http://dx.doi.org/10.1002/acm2.13853
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